improved doc formatting by fixing indentation and escape characters

lib/axon.ex

@@ -143,7 +143,7 @@ defmodule Axon do
  parameters and possibly state. To define a custom layer, you just need to
  define a `defn` implementation:
 
- defn my_layer(x, weight, _opts \\ []) do
+ defn my_layer(x, weight, _opts \\\\ []) do
  Nx.atan2(x, weight)
  end
 

lib/axon/layers.ex

@@ -1457,7 +1457,7 @@ defmodule Axon.Layers do
  * `:rate` - dropout rate. Used to determine probability a connection
  will be dropped. Required.
 
- # `:noise_shape` - input noise shape. Shape of `mask` which can be useful
+ * `:noise_shape` - input noise shape. Shape of `mask` which can be useful
  for broadcasting `mask` across feature channels or other dimensions.
  Defaults to shape of input tensor.
 
@@ -1492,7 +1492,7 @@ defmodule Axon.Layers do
  * `:rate` - dropout rate. Used to determine probability a connection
  will be dropped. Required.
 
- # `:noise_shape` - input noise shape. Shape of `mask` which can be useful
+ * `:noise_shape` - input noise shape. Shape of `mask` which can be useful
  for broadcasting `mask` across feature channels or other dimensions.
  Defaults to shape of input tensor.
 
@@ -1536,7 +1536,7 @@ defmodule Axon.Layers do
  * `:rate` - dropout rate. Used to determine probability a connection
  will be dropped. Required.
 
- # `:noise_shape` - input noise shape. Shape of `mask` which can be useful
+ * `:noise_shape` - input noise shape. Shape of `mask` which can be useful
  for broadcasting `mask` across feature channels or other dimensions.
  Defaults to shape of input tensor.
  """

lib/axon/loop.ex

@@ -186,13 +186,13 @@ defmodule Axon.Loop do
  Axon loops are typically created from one of the factory functions provided in this
  module:
 
-  * `Axon.Loop.loop/3` - Creates a loop from step function and optional initialization
+ * `Axon.Loop.loop/3` - Creates a loop from step function and optional initialization
  functions and output transform functions.
 
-  * `Axon.Loop.trainer/3` - Creates a supervised training loop from model, loss, and
+ * `Axon.Loop.trainer/3` - Creates a supervised training loop from model, loss, and
  optimizer.
 
-  * `Axon.Loop.evaluator/1` - Creates a supervised evaluator loop from model.
+ * `Axon.Loop.evaluator/1` - Creates a supervised evaluator loop from model.
 
  ## Running loops
 

lib/axon/metrics.ex

@@ -38,8 +38,8 @@ defmodule Axon.Metrics do
 
  ## Argument Shapes
 
- * `y_true` - $\(d_0, d_1, ..., d_n\)$
- * `y_pred` - $\(d_0, d_1, ..., d_n\)$
+ * `y_true` - $(d_0, d_1, ..., d_n)$
+ * `y_pred` - $(d_0, d_1, ..., d_n)$
 
  ## Examples
 
@@ -96,8 +96,8 @@ defmodule Axon.Metrics do
 
  ## Argument Shapes
 
- * `y_true` - $\(d_0, d_1, ..., d_n\)$
- * `y_pred` - $\(d_0, d_1, ..., d_n\)$
+ * `y_true` - $(d_0, d_1, ..., d_n)$
+ * `y_pred` - $(d_0, d_1, ..., d_n)$
 
  ## Options
 
@@ -127,8 +127,8 @@ defmodule Axon.Metrics do
 
  ## Argument Shapes
 
- * `y_true` - $\(d_0, d_1, ..., d_n\)$
- * `y_pred` - $\(d_0, d_1, ..., d_n\)$
+ * `y_true` - $(d_0, d_1, ..., d_n)$
+ * `y_pred` - $(d_0, d_1, ..., d_n)$
 
  ## Options
 
@@ -285,8 +285,8 @@ defmodule Axon.Metrics do
 
  ## Argument Shapes
 
- * `y_true` - $\(d_0, d_1, ..., d_n\)$
- * `y_pred` - $\(d_0, d_1, ..., d_n\)$
+ * `y_true` - $(d_0, d_1, ..., d_n)$
+ * `y_pred` - $(d_0, d_1, ..., d_n)$
 
  ## Options
 
@@ -314,8 +314,8 @@ defmodule Axon.Metrics do
 
  ## Argument Shapes
 
- * `y_true` - $\(d_0, d_1, ..., d_n\)$
- * `y_pred` - $\(d_0, d_1, ..., d_n\)$
+ * `y_true` - $(d_0, d_1, ..., d_n)$
+ * `y_pred` - $(d_0, d_1, ..., d_n)$
 
  ## Options
 
@@ -359,8 +359,8 @@ defmodule Axon.Metrics do
 
  ## Argument Shapes
 
- * `y_true` - $\(d_0, d_1, ..., d_n\)$
- * `y_pred` - $\(d_0, d_1, ..., d_n\)$
+ * `y_true` - $(d_0, d_1, ..., d_n)$
+ * `y_pred` - $(d_0, d_1, ..., d_n)$
 
  ## Examples
 
@@ -390,8 +390,8 @@ defmodule Axon.Metrics do
 
  ## Argument Shapes
 
- * `y_true` - $\(d_0, d_1, ..., d_n\)$
- * `y_pred` - $\(d_0, d_1, ..., d_n\)$
+ * `y_true` - $(d_0, d_1, ..., d_n)$
+ * `y_pred` - $(d_0, d_1, ..., d_n)$
 
  ## Examples